Amazon S3
7 use cases using this technology
GoGuardian: Safer schools, empowered teachers, thriving students
GoGuardian
GoGuardian, which powers safe, focused learning for half of U.S. K-12 students, migrated its ML infrastructure to Databricks to manage billions of daily inferences for web filtering, classroom management and harm prevention while maintaining a PII-free, COPPA/FERPA-compliant data environment. Using Delta Lake, Lakeflow, Unity Catalog, MLflow and Databricks Model Serving, GoGuardian achieved up to 50% reduction in machine learning operational costs, 90% operational cost savings with its Delphi website classification model, and a 62% reduction in inappropriate device use among students. AI-driven prioritization also cut the volume of records requiring human review for high-risk content by over 95%, from 1 million to 35,000-45,000.
Siemens Electronics Factory Erlangen Reduces Machine Learning Deployment Time by 80% with AWS and Siemens Industrial AI on Industrial Edge
Siemens Electronics Factory Erlangen
Siemens Electronics Factory Erlangen, which manufactures PCBs and controllers such as SINAMICS converters and SINUMERIK CNC controllers, used computer vision models to spot anomalies in PCB assembly, but training and retraining ML models on premises was time-intensive and constrained by GPU bottlenecks. The factory adopted AWS services together with Siemens Industrial Edge and Siemens Industrial AI, sending shopfloor images via Edge applications to Amazon S3 before training via Amazon SageMaker or AWS Lambda; training results and edge prediction results are monitored through AI Model Monitor, with AI Model Manager providing central management of models on the shopfloor. This reduced time spent on model training and retraining by 80 percent (from about 30 minutes to roughly 5 minutes for retraining and deployment), cut costs by more than 90 percent compared to on-premises data storage systems, and reduced the false call rate by over 50 percent, while continuously preventing around 4 percent of PCB assembly errors compared to around 60 percent at peaks in the past.
Contra Costa County District Attorney's Office Makes Unbiased Charging Decisions with ScaleCapacity Generative AI Solution on AWS
Contra Costa County District Attorney's Office
The Contra Costa County District Attorney's Office worked with AWS Partner ScaleCapacity to build a Race-Blind Charging solution to comply with California's AB 2778 mandate. The solution uses Amazon Bedrock and Amazon Textract to automatically redact race, ethnicity and other identifying details from police reports and case documents before charging decisions are made, with Amazon S3, DynamoDB, Cognito and SES supporting document storage, metadata and user access. The office processes around 17,000 cases annually, achieved compliance in six months, and can test and deploy new redaction rule changes in under a week.
Figma trains AI Search models in 5 months using Amazon SageMaker AI
Figma
Design platform Figma built its AI infrastructure on Amazon SageMaker AI, using Amazon EMR with Apache Spark to process billions of design elements and the custom FigmaStep framework on SageMaker Pipelines to orchestrate training. Figma trained and deployed the models behind its AI Search feature within five months, launching it at Config 2024, and ran more than 10,000 SageMaker AI training jobs in 2025 to support features including the AI prompt-to-app tool Figma Make.
Phagos uses generative AI on AWS to match bacteriophages to bacterial infections
Phagos
Phagos, a Paris-based biotech startup, uses generative AI models built with Amazon SageMaker AI to match bacteriophages to target bacteria for phage therapy, replacing a manual trial-and-error process. The AI models cut wet-lab testing needs by 50% and reduced phage-candidate screening time by 99.5%, from 29 hours to 10 minutes per bacteria. Phagos has treated more than half a million animals in France and can now develop a new treatment in two months versus 10+ years for traditional antibiotic development.
Forcura Expedites Patient Care Using Generative AI on Amazon Bedrock
Forcura
Forcura, a HITRUST-certified healthcare workflow management company serving over 900 healthcare providers representing about 1 million patients, added a generative-AI referral summary feature to its Referral Management product. Built on Amazon Bedrock using Anthropic's Claude 3 model family, the feature pulls key information such as patient demographics, clinical history and requested services into a concise summary. Forcura piloted the feature with three clients in April 2024 and reached general release within 90 days of the pilot start.
Novartis: Accelerating Drug Development with AI-Powered Clinical Trial Transformation
Novartis
Novartis partnered with AWS Professional Services and Accenture to modernize their drug development infrastructure and integrate AI across clinical trials, with the goal of reducing trial development cycles by at least six months. The initiative built a GXP-compliant data mesh platform on AWS with Databricks for processing, enabling AI use cases including protocol generation and an intelligent decision system (digital twin). Early results from the patient safety domain showed 72% query speed improvements, 60% storage cost reduction, and 160+ hours of manual work eliminated. The protocol generation use case achieved 83-87% acceleration in producing compliant protocols.